Channel impulse response summation method based on frequency domain sliding window cross-correlation operation

Abstract

The application discloses a channel impulse response summation method based on a frequency domain sliding window cross-correlation operation, and belongs to the field of wireless communication.The application solves the problem that the existing method needs to utilize a complex search and calculation process to restore a channel state information matrix.In a time-selective fading channel with an integer Doppler frequency shift and a fractional Doppler frequency shift, the application extracts a Doppler frequency shift feature through a sliding correlation between a locally stored signal and a received signal, utilizes Dirichlet compensation to eliminate the influence of an alternating phase, and averages channel influence through a frequency domain window summation process.The frequency domain window summation process can aggregate a Dirichlet energy dispersion effect caused by the fractional Doppler frequency shift, thereby reducing the influence of frequency shift expansion on channel estimation and receiving demodulation.The application does not need to accurately distinguish a channel Doppler and a channel gain to restore channel state information, and can reduce the calculation complexity of a receiving end channel estimation and a receiving process.The application can be applied to the field of wireless communication.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication, specifically relating to a channel impulse response summation (SCIR-FSWCC) method based on frequency domain sliding window cross-correlation. Background Technology

[0002] As the next-generation mobile communication technology 6G evolves towards an integrated space-ground communication network architecture, the wireless air interface technology in space-ground networks has become a widely discussed topic. However, satellites in non-terrestrial networks (NTNs) are characterized by high-speed movement, resulting in extremely high Doppler frequency shift characteristics in space-ground communication systems. In time-selective fading channels, the channel changes rapidly, severely disrupting the orthogonality of Orthogonal Frequency Division Multiplexing (OFDM) systems. In recent years, the Orthogonal Chirp Division Multiplexing (OCDM) waveform proposed in reference 1 (X. Ouyang and J. Zhao, "Orthogonal Chirp Division Multiplexing," IEEE Transactions on Communications, vol. 64, no. 9, pp. 3946-3957, Sept. 2016.) is a promising technical solution for NTN scenarios. The system uses the Chirp signal as the carrier substrate. Due to the spreading characteristics of the Chirp signal, it exhibits strong robustness to Doppler frequency shift.

[0003] In multicarrier systems, the Doppler shift is normalized relative to the subcarrier spacing, and is categorized into integer Doppler shift and fractional Doppler shift. Integer Doppler shift leads to a cyclic shift of the subcarrier index, while fractional Doppler shift results in severe inter-carrier interference (ICI), degrading system performance. Therefore, accurate channel estimation is crucial for subsequent reception and demodulation in wireless communication systems.

[0004] Existing channel estimation methods all attempt to estimate the delay, Doppler shift, and channel complex gain of each transmission path to recover the Channel State Information (CSI) matrix, which requires a complex search and calculation process. For example, Reference 2 (Y. Wang, R. Zhang, L. Yan, and X. Ma, "Pilot chirp-assisted OCDM communications over time-varying channels," IEEE Wireless Communications Letters, vol. 12, no. 9, pp. 1578-1582, Sep. 2023.) proposes a chirp-assisted channel estimation method and develops a channel estimator with minimum mean square error (MMSE), but it involves high computational complexity. References 3 (SE Zegrar and H. Arslan, "A novel delay-Doppler-based channel estimation method in doubly-dispersive OCDM systems," IEEE Wireless Communications Letters, vol. 13, no. 3, pp. 801-804, Mar. 2024.) and 4 (Z. Du, L. Mei, X. Lin, Z. Li, and B. Zhang, "A novel embedded The paper "Pilot-aided OCDM system over time-varying channels" (IEEE Communications Letters, vol. 28, no. 11, pp. 2643-2647, Nov. 2024) proposes a method for low-complexity pilot design and low pilot overhead. However, it only considers the influence of integer Doppler in the channel estimation process, which limits its practicality in real-world scenarios. Summary of the Invention

[0005] The purpose of this invention is to solve the problem that existing receiving and demodulation methods require complex search and calculation processes to recover the channel state information matrix, and to propose a channel impulse response summation method based on frequency domain sliding window cross-correlation operation.

[0006] The technical solution adopted by this invention to solve the above-mentioned technical problems is: a channel impulse response summation method based on frequency domain sliding window cross-correlation operation, the method specifically including the following steps:

[0007] At the transmitting end:

[0008] Step 1: Based on the index interval between adjacent valid subcarriers To determine the index set of effective subcarriers in the system. :

[0009] (1)

[0010] in:

[0011] Represents a set The subcarrier position of the first valid subcarrier in the system. The value is This indicates that the first effective subcarrier is the first effective subcarrier in the system. Subcarriers;

[0012] Represents a set The subcarrier position of the second effective subcarrier in the system. The value is This indicates that the second effective subcarrier is the first effective subcarrier in the system. Subcarriers;

[0013] Represents a set The first in The subcarrier positions of the effective subcarriers in the system. The value is , indicating the first The effective subcarrier is the system's... Subcarriers;

[0014] In the set In this process, the first valid subcarrier is allocated as a pilot subcarrier for transmitting known pilot symbols. The remaining valid subcarriers are all allocated as data subcarriers for transmitting data symbols. ;

[0015] Step 2: Generate the Chirp basis function for each effective subcarrier. Modulate the pilot symbols and data symbols onto the Chirp basis function of the corresponding subcarrier, and then linearly superimpose the modulation results in the time domain to obtain the linearly superimposed signal.

[0016] Step 3: After adding a cyclic prefix to the linear superimposed signal, perform parallel-to-serial conversion to obtain the baseband transmit signal, and then transmit the baseband transmit signal through the time-selective fading channel;

[0017] At the receiving end:

[0018] Step 4: After the baseband transmitted signal passes through the time-selective fading channel, it undergoes serial-to-parallel conversion and cyclic prefix removal to obtain the received signal. and the received signal Perform a fast Fourier transform to obtain the frequency domain signal. ;

[0019] Step 5: Perform a Fast Fourier Transform on the locally stored pilot subcarrier Chirp basis functions to obtain the frequency response of the pilot Chirp basis functions;

[0020] Frequency response and frequency domain signal of pilot Chirp basis functions Perform frequency domain sliding window cross-correlation to obtain the frequency domain sliding window cross-correlation results;

[0021] Step 6: Perform Dirichlet compensation on the frequency domain sliding window cross-correlation results to obtain the compensated results;

[0022] Step 7: Summate the compensation results within the Doppler energy spread window to obtain the pilot summation result; divide the pilot summation result by the locally known pilot symbols to obtain the estimated channel impulse response. ;

[0023] Step 8: Calculate the summation result of each data subcarrier within its own Doppler energy spread window using the methods from Steps 5 to 7.

[0024] The summation result for each data subcarrier is compared with the estimated channel impulse response and... Divide them to obtain the demodulated data:

[0025] (18)

[0026] in, For the demodulated first Data transmitted by each data subcarrier For the first The summation of each data subcarrier within its own Doppler energy spread window.

[0027] Furthermore, the index interval for:

[0028]

[0029] in, This represents the maximum Doppler frequency shift.

[0030] Furthermore, the number of effective subcarriers is , Indicates rounding down. This indicates the total number of subcarriers.

[0031] Furthermore, for pilot subcarriers:

[0032] (2)

[0033] in, The Chirp basis functions are for the pilot subcarriers. for The One sampling point, is the base of the natural logarithm. The imaginary unit;

[0034] For data subcarriers:

[0035] (3)

[0036] in, For the first Chirp basis functions for each data subcarrier for The One sampling point.

[0037] Furthermore, the specific process of step 2 is as follows:

[0038] (4)

[0039] in, Linear superposition signal The One sampling point, For the first Each data subcarrier needs to transmit data symbols.

[0040] Furthermore, the received signal for:

[0041] (5)

[0042] in, For the first in the channel Complex gain of the path, For the first in the channel Normalized Doppler frequency shift of the path, , This represents the total number of paths in the channel. It is additive white Gaussian noise. To receive signals The first in One sampling point;

[0043] (6)

[0044] in, For the first Integer Doppler shift of the path, For the first The fractional Doppler shift of the path.

[0045] Furthermore, the frequency domain signal for:

[0046] (7)

[0047] in, Frequency domain signal The first in Each frequency domain sampling point.

[0048] Furthermore, the specific process of step 5 is as follows:

[0049] Performing a Fast Fourier Transform on the locally stored pilot subcarrier Chirp basis functions yields the frequency response of the pilot Chirp basis functions:

[0050] (8)

[0051] in, Represents the Fast Fourier Transform. The first term in the frequency response of the pilot Chirp basis function represents the... One frequency domain sampling point;

[0052] Frequency response and frequency domain signal of pilot Chirp basis functions Perform frequency domain sliding window cross-correlation to obtain the frequency domain sliding window cross-correlation results. ;

[0053] (9)

[0054] in, The first of the frequency responses of the pilot Chirp basis functions Each frequency domain sampling point Modulus Operations, For discrete Doppler search variables (i.e., relative frequency shift variables), and Doppler energy diffusion window Internal search, window range is , Indicates conjugate;

[0055] According to Passevar's theorem, equation (9) can be equivalent to time-domain computation:

[0056] (10)

[0057] Based on equations (4) and (5), equation (10) can be transformed into:

[0058] (11)

[0059] Then, approximate equation (11) as follows:

[0060] (12)

[0061] Equation (12) can be simplified to a closed-form solution containing the discrete Dirichlet kernel:

[0062] (13).

[0063] Furthermore, the specific process of step 6 is as follows:

[0064] (14)

[0065] in, This is the result after compensation.

[0066] Furthermore, the specific process of step 7 is as follows:

[0067] The compensation results are summed within the Doppler energy diffusion window to obtain the pilot summation result;

[0068] (15)

[0069] in, To obtain the summation result;

[0070] Sum result Dividing by the known local pilot symbols yields the estimated channel impulse response:

[0071] (16)

[0072] in, Let be the estimated channel impulse response and .

[0073] The beneficial effects of this invention are:

[0074] This invention proposes a channel impulse response summation method based on frequency-domain sliding window cross-correlation, utilizing the characteristics of Chirp signals. In time-selective fading channels with both integer and fractional Doppler shifts, this method extracts Doppler shift features through the sliding correlation between the locally stored signal and the received signal, eliminates the influence of alternating phases using Dirichlet compensation, and averages channel effects through a frequency-domain window summation process. The frequency-domain window summation process aggregates the Dirichlet energy dispersion effect caused by fractional Doppler shifts, thereby reducing the impact of shift spread on channel estimation and demodulation. This method eliminates the need for accurate differentiation of channel Doppler and channel gain to recover channel state information, reducing the computational complexity of channel estimation and reception at the receiver, making it suitable for engineering implementation. Attached Figure Description

[0075] Figure 1 This is a flowchart of the method of the present invention at the transmitting end;

[0076] Figure 2 This is a flowchart of the method of the present invention at the receiving end;

[0077] Figure 3 Is when Comparison of BER performance under integer Doppler frequency shift and fractional Doppler frequency shift conditions;

[0078] Figure 4 Is when The graph shows a comparison of BER performance under the conditions of integer Doppler shift and fractional Doppler shift. Detailed Implementation

[0079] Specific Implementation Method 1: Combination Figure 1 and Figure 2 This embodiment describes a channel impulse response summation method based on frequency domain sliding window cross-correlation. The method specifically includes the following steps:

[0080] At the transmitting end:

[0081] Step 1: Based on the index interval between adjacent valid subcarriers To determine the index set of effective subcarriers in the system. ;

[0082] Specifically, to avoid ICI caused by Doppler leakage overlap, the present invention sets an index interval between adjacent effective subcarriers. ,in, The maximum Doppler frequency shift;

[0083] The number of effective subcarriers in the system is , Indicates rounding down. Represents the total number of subcarriers; the set of indices of valid subcarriers in the system. for:

[0084] (1)

[0085] in:

[0086] Represents a set The subcarrier position of the first valid subcarrier in the system. The value is This indicates that the first effective subcarrier is the first effective subcarrier in the system. Subcarriers;

[0087] Represents a set The subcarrier position of the second effective subcarrier in the system. The value is This indicates that the second effective subcarrier is the first effective subcarrier in the system. Subcarriers;

[0088] Represents a set The first in The subcarrier positions of the effective subcarriers in the system. The value is , indicating the first The effective subcarrier is the system's... Subcarriers;

[0089] In the set In this process, the first valid subcarrier is allocated as a pilot subcarrier for transmitting known pilot symbols. The remaining valid subcarriers are all allocated as data subcarriers for transmitting data symbols. , Sets The second effective subcarrier, the third effective subcarrier, ..., the ... The data symbols that need to be transmitted for each effective subcarrier, with the superscript T indicating transpose;

[0090] Step 2: OCDM can generate the Chirp basis function for each effective subcarrier by inverse discrete Fresnel transform (IDFnT) modulation, and the Chirp basis functions of each effective subcarrier satisfy the cyclic shift property.

[0091] For pilot subcarriers:

[0092] (2)

[0093] in, The Chirp basis functions are for the pilot subcarriers. for The One sampling point, is the base of the natural logarithm. The imaginary unit;

[0094] For data subcarriers:

[0095] (3)

[0096] in, For the first Chirp basis functions for each data subcarrier for The One sampling point;

[0097] Multiply the Chirp basis function of the effective subcarrier with the information to be transmitted on the effective subcarrier. That is, modulate the pilot symbols and data symbols onto the Chirp basis function of the corresponding subcarrier respectively, and then linearly superimpose the modulation results in the time domain:

[0098] (4)

[0099] in, Linear superposition signal The One sampling point, For the first Each data subcarrier needs to transmit data symbols;

[0100] Step 3: After adding a cyclic prefix to the linear superimposed signal, perform parallel-to-serial conversion to obtain the baseband transmission signal, and then transmit the baseband transmission signal through a time-selective fading channel with different Doppler frequency shifts.

[0101] To achieve CSI estimation and data demodulation, this invention proposes an SCIR-FSWCC method to realize channel estimation and reception based on channel impulse response summation. At the receiving end:

[0102] Step 4: After the baseband transmitted signal passes through the time-selective fading channel, it undergoes serial-to-parallel conversion and cyclic prefix removal to obtain the received signal. for:

[0103] (5)

[0104] in, For the first in the channel Complex gain of the path, For the first in the channel Normalized Doppler frequency shift of the path, , This represents the total number of paths in the channel. It is additive white Gaussian noise. To receive signals The first in One sampling point;

[0105] (6)

[0106] in, For the first Integer Doppler shift of the path, For the first The fractional Doppler shift of the path;

[0107] For the received signal Perform a Fast Fourier Transform (FFT) to obtain the frequency domain signal. :

[0108] (7)

[0109] in, Frequency domain signal The first in One frequency domain sampling point;

[0110] The matrix rows and columns of the Discrete Fresnel Transform (DFnT) have ZC sequence properties, and these properties are retained after FFT. Based on this, the present invention proposes the following processing procedure.

[0111] Step 5: Perform a Fast Fourier Transform on the locally stored pilot subcarrier Chirp basis functions to obtain the frequency response of the pilot Chirp basis functions:

[0112] (8)

[0113] in, Represents the Fast Fourier Transform. The first term in the frequency response of the pilot Chirp basis function represents the... One frequency domain sampling point;

[0114] Frequency response and frequency domain signal of pilot Chirp basis functions Perform frequency domain sliding window cross-correlation (FSWCC) to obtain the frequency domain sliding window cross-correlation results. ;

[0115] Specifically,

[0116] (9)

[0117] in, The first of the frequency responses of the pilot Chirp basis functions Each frequency domain sampling point Modulus Operations, For discrete Doppler search variables (i.e., relative frequency shift variables), and Doppler energy diffusion window Internal search, window range is , Indicates conjugate;

[0118] According to Passevar's theorem, equation (9) can be equivalent to time-domain computation:

[0119] (10)

[0120] Based on equations (4) and (5), equation (10) can be transformed into:

[0121] (11)

[0122] in, We ignore the noise term. Since the Chirp basis functions exhibit good low cross-correlation across different subcarriers, when the index interval between adjacent effective carriers is sufficient, the cross-interference term after summing the data basis and pilot basis sequences can be ignored, i.e. .

[0123] Therefore, equation (11) can be approximated as:

[0124] (12)

[0125] Observing the bracketed part of equation (12), equation (12) can be simplified into a closed-form solution containing the discrete Dirichlet kernel:

[0126] (13)

[0127] Step 6: In order to eliminate the frequency shift variable in equation (13) The resulting alternating negative phases need to be multiplied by a compensation factor to construct the pre-sum sign, i.e., Dirichlet compensation (DC) is performed on the frequency domain sliding window cross-correlation result. The compensated result is as follows:

[0128] (14)

[0129] in, The result after compensation;

[0130] Step 7: Sum the compensation results within the Doppler energy diffusion window to obtain the pilot summation result;

[0131] (15)

[0132] in, To obtain the summation result;

[0133] Sum result Dividing by the locally known pilot symbols yields the estimated channel impulse response (SCIR):

[0134] (16)

[0135] in, The estimated channel impulse response and;

[0136] Step 8: Calculate the summation result of each data subcarrier within its own Doppler energy spread window using the methods from Steps 5 to 7.

[0137] (17)

[0138] in, For the first The summation result of each data subcarrier within its own Doppler energy spread window;

[0139] The summation result for each data subcarrier is compared with the estimated channel impulse response and... Divide them to obtain the demodulated data:

[0140] (18)

[0141] in, For the demodulated first Data transmitted by each data subcarrier.

[0142] The following uses the first data subcarrier as an example. Taking this as an example, the method for calculating the summation result of the first data subcarrier within its own Doppler energy diffusion window is as follows:

[0143] First, the data subcarriers stored locally. The data subcarriers are obtained by performing a Fast Fourier Transform on the Chirp basis functions. Frequency response of Chirp basis functions :

[0144] (19)

[0145] Frequency response and frequency domain signals Perform frequency domain sliding window cross-correlation;

[0146] (20)

[0147] in, Modulus Operations, For discrete Doppler search variables, and Within the Doppler energy diffusion window Internal search, for The conjugate;

[0148] According to Passevar's theorem, equation (20) can be equivalent to a time-domain computation:

[0149] (twenty one)

[0150] Based on equations (4) and (5), equation (21) can be transformed into:

[0151] (twenty two)

[0152] in, We ignore the noise term. Since the Chirp basis functions have good low cross-correlation across different subcarriers, the cross-interference term after summing the data basis and pilot basis sequences can be ignored when the index interval between adjacent effective carriers is sufficient. (First term) The second term indicates the interference of the pilot signal on the current data carrier. The third term represents the useful signal energy of the current data subcarrier. This indicates cross-interference from other data subcarriers to the current data subcarrier. The first and third terms can be ignored after summing.

[0153] Therefore, equation (22) can be approximated as

[0154] (twenty three)

[0155] Observing the part in brackets of equation (23), equation (23) can be simplified into a closed-form solution containing a discrete Dirichlet kernel:

[0156] (twenty four)

[0157] In order to eliminate the frequency shift variable in equation (24) The resulting alternating negative phases need to be multiplied by a compensation factor to construct the pre-sum sign, i.e., Dirichlet compensation (DC) is performed on the frequency domain sliding window cross-correlation result. The compensated result is as follows:

[0158] (25)

[0159] in, The result after compensation;

[0160] The compensation results are summed within the Doppler energy diffusion window to obtain the data subcarrier. The corresponding summation result ;

[0161] (26)

[0162] Simulation section

[0163] An ideal channel is defined as a perfect CSI with no estimation error, and the simulation assumes that the channel gain of the path follows a complex Gaussian distribution. The total number of subcarriers... The constellation mapping method is 4-QAM, and the number of paths is... Consider the following time-selective fading channel models: one is an integer Doppler shift channel, and the other is a fractional Doppler shift channel.

[0164] Among them, the integer normalized Doppler frequency shift values ​​are respectively The decimal normalized Doppler frequency shift values ​​are respectively Define the index interval between adjacent valid subcarriers. Greater than the maximum Doppler frequency shift value, set Pilot power is .

[0165] when The performance of the ideal channel model, the method of the present invention in a time-selective fading channel model with integer and fractional Doppler frequency shifts, and the method of the present invention without DC compensation in a time-selective fading channel model with integer and fractional Doppler frequency shifts were compared. Figure 3 It can be seen that if DC compensation is not performed before summation, there is basically no impact on integer Doppler shift channels, but the performance of fractional Doppler shift channels deteriorates sharply. This is because energy diffuses to adjacent subcarriers, and direct summation causes severe destructive interference of the energy diffused on the main lobe and side lobes. Furthermore, the method of this invention exhibits a certain performance gap for ZF equalization under ideal channel conditions, due to the influence of superimposed noise.

[0166] when The performance of the ideal channel model and the method of this invention in a time-selective fading channel model with integer Doppler shift and fractional Doppler shift was compared. Figure 4 It can be seen that the performance of the SCIR-FSWCC method of this invention differs somewhat between integer Doppler frequency shift channels and fractional Doppler frequency shift channels. This is because, with... The reduction in frequency shift causes the energy diffusion effect of the fractional Doppler shift to extend to adjacent subcarriers, resulting in some performance loss. Therefore, it is important to rationally select the window to cover the Doppler energy diffusion. Index interval with adjacent effective subcarriers This ensures system performance.

[0167] The above examples of the present invention are merely illustrative of the computational model and process of the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is impossible to exhaustively list all possible implementations here. Any obvious variations or modifications derived from the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for summing channel impulse responses based on frequency-domain sliding window cross-correlation, characterized in that, The method specifically includes the following steps: At the transmitting end: Step 1: Based on the index interval between adjacent valid subcarriers To determine the index set of effective subcarriers in the system. : （1） in: Represents a set The subcarrier position of the first valid subcarrier in the system. The value is This indicates that the first effective subcarrier is the first effective subcarrier in the system. Subcarriers; Represents a set The subcarrier position of the second effective subcarrier in the system. The value is This indicates that the second effective subcarrier is the first effective subcarrier in the system. Subcarriers; Represents a set The first in The subcarrier positions of the effective subcarriers in the system. The value is , indicating the first The effective subcarrier is the system's... Subcarriers; In the set In this process, the first valid subcarrier is allocated as a pilot subcarrier for transmitting known pilot symbols. The remaining valid subcarriers are all allocated as data subcarriers for transmitting data symbols. ; Step 2: Generate the Chirp basis function for each effective subcarrier. Modulate the pilot symbols and data symbols onto the Chirp basis function of the corresponding subcarrier, and then linearly superimpose the modulation results in the time domain to obtain the linearly superimposed signal. Step 3: After adding a cyclic prefix to the linear superimposed signal, perform parallel-to-serial conversion to obtain the baseband transmit signal, and then transmit the baseband transmit signal through the time-selective fading channel; At the receiving end: Step 4: After the baseband transmitted signal passes through the time-selective fading channel, it undergoes serial-to-parallel conversion and cyclic prefix removal to obtain the received signal. and the received signal Perform a fast Fourier transform to obtain the frequency domain signal. ; Step 5: Perform a Fast Fourier Transform on the locally stored pilot subcarrier Chirp basis functions to obtain the frequency response of the pilot Chirp basis functions; Frequency response and frequency domain signal of pilot Chirp basis functions Perform frequency domain sliding window cross-correlation to obtain the frequency domain sliding window cross-correlation results; Step 6: Perform Dirichlet compensation on the frequency domain sliding window cross-correlation results to obtain the compensated results; Step 7: Summate the compensation results within the Doppler energy spread window to obtain the pilot summation result; divide the pilot summation result by the locally known pilot symbols to obtain the estimated channel impulse response. ; Step 8: Calculate the summation result of each data subcarrier within its own Doppler energy spread window using the methods from Steps 5 to 7. The summation result for each data subcarrier is compared with the estimated channel impulse response and... Divide them to obtain the demodulated data: （18） in, For the demodulated first Data transmitted by each data subcarrier For the first The summation of each data subcarrier within its own Doppler energy spread window.

2. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 1, characterized in that, The index interval for: in, This represents the maximum Doppler frequency shift.

3. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 2, characterized in that, The number of effective subcarriers is , Indicates rounding down. This indicates the total number of subcarriers.

4. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 3, characterized in that, For pilot subcarriers: （2） in, The Chirp basis functions are for the pilot subcarriers. for The One sampling point, is the base of the natural logarithm. The imaginary unit; For data subcarriers: （3） in, For the first Chirp basis functions for each data subcarrier for The One sampling point.

5. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 4, characterized in that, The specific process of step 2 is as follows: （4） in, Linear superposition signal The One sampling point, For the first Each data subcarrier needs to transmit data symbols.

6. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 5, characterized in that, The received signal for: （5） in, For the first in the channel Complex gain of the path, For the first in the channel Normalized Doppler frequency shift of the path, , This represents the total number of paths in the channel. It is additive white Gaussian noise. To receive signals The first in One sampling point; （6） in, For the first Integer Doppler shift of the path, For the first The fractional Doppler shift of the path.

7. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 6, characterized in that, The frequency domain signal for: （7） in, Frequency domain signal The first in Each frequency domain sampling point.

8. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 7, characterized in that, The specific process of step 5 is as follows: Performing a Fast Fourier Transform on the locally stored pilot subcarrier Chirp basis functions yields the frequency response of the pilot Chirp basis functions: （8） in, Represents the Fast Fourier Transform. The first term in the frequency response of the pilot Chirp basis function represents the... One frequency domain sampling point; Frequency response and frequency domain signal of pilot Chirp basis functions Perform frequency domain sliding window cross-correlation to obtain the frequency domain sliding window cross-correlation results. ; （9） in, The first of the frequency responses of the pilot Chirp basis functions Each frequency domain sampling point Modulus Operations, For discrete Doppler search variables, and Doppler energy diffusion window Internal search, window range is , Indicates conjugate; According to Passevar's theorem, equation (9) is equivalent to time-domain computation: （10） Based on equations (4) and (5), equation (10) can be transformed into: （11） Then, approximate equation (11) as follows: （12） Equation (12) can be simplified to a closed-form solution containing the discrete Dirichlet kernel: （13）。 9. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 8, characterized in that, The specific process of step 6 is as follows: （14） in, This is the result after compensation.

10. The channel impulse response summation method based on frequency domain sliding window cross-correlation operation according to claim 9, characterized in that, The specific process of step 7 is as follows: The compensation results are summed within the Doppler energy diffusion window to obtain the pilot summation result; （15） in, To obtain the summation result; Sum result Dividing by the known local pilot symbols yields the estimated channel impulse response: （16） in, Let be the estimated channel impulse response and .

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